Business Intel Engineer II, SPT Analytics

As we strive to be Earth's most customer-centric company, Amazon has reinvented how hundreds of millions of people shop online – providing customers with the opportunity to find and discover virtually anything they want to buy and providing millions of sellers with a platform for growing successful businesses. We are looking for an exceptional Business Intelligence Engineer to help us develop new ways to build trust and loyalty with sellers, a crucial component of our flywheel.

Sellers' trust in Amazon is our top priority and in this role, you will be tasked with building that trust over time by developing and maintaining analytical solutions that drive key business decisions. Amazon's growth requires analytical leaders who move fast, have an entrepreneurial spirit to create new insights, have an unrelenting tenacity to get things done, and are capable of breaking down and solving complex business problems through data-driven solutions.

The successful candidate will be a self-starter, comfortable with ambiguity and be able to create and maintain efficient & automated reporting frameworks. They know and love working with SQL and business intelligence tools, can analyze multidimensional datasets, and can partner effectively with business leaders to answer key business questions. They will build efficient, insightful dashboards, metrics, and analytical solutions while maintaining data quality and documentation. They will also be required to support and manage the growth of these analytical solutions.

They are analytical and creative, and don't quit. This role offers high visibility to senior leadership and significant opportunity for impact for those willing to roll up their sleeves and dive deep into data to achieve results. The position requires someone who can translate business needs into analytical solutions while maintaining strong partnerships across teams.

Key job responsibilities
- Design and implement scalable data architecture and analytics pipelines using AWS services, creating robust ETL processes and optimized data models to support enterprise reporting needs
- Build automated, self-service reporting capabilities and dashboards using BI tools like QuickSight, enabling stakeholders to independently access insights and address business questions
- Partner with cross-functional teams (BAs, Data Engineers, Product Managers) to gather requirements, translate business needs into technical solutions, and deliver high-quality data products
- Develop and optimize complex SQL queries and stored procedures while implementing data quality frameworks to ensure accuracy and reliability of analytics solutions
- Conduct advanced statistical analysis and create analytical models to uncover trends, develop insights, and support data-driven decision making
- Identify and implement process improvements through automation, code optimization, and integration of generative AI capabilities to enhance BI processes and reporting efficiency
- Lead technical discussions, provide mentorship to junior team members, and present solutions to stakeholders while staying current with emerging technologies and best practices

A day in the life
As a Business Intelligence Engineer in the Selling Partner Trust Analytics team, you'll develop analytical solutions to provide insights into Emerging Markets seller experience and measure global technical support initiatives. You'll transform operational data into actionable insights for leaders and engineers worldwide, managing critical datasets for support metrics, productivity, and customer satisfaction.

Key responsibilities include building real-time dashboards, automated reporting systems, and data quality frameworks. You'll work with stakeholders to implement analytics solutions and drive data-driven decision-making. The role involves optimizing query performance and translating findings into recommendations to improve support efficiency and customer experience.

- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with data modeling, warehousing and building ETL pipelines
- Experience in Statistical Analysis packages such as R, SAS and Matlab
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling

- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets

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